Abstract
This chapter provides an answer to the question: What it is, philosophically speaking, to choose a model in a statistical procedure, and what does this amounts to in the context of a Bayesian inference? Special attention is given to Bayesian model selection, specifically the choice between inequality constrained and unconstrained models based on their Bayes factors and posterior model probabilities.
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Romeijn, JW., van de Schoot, R. (2008). A Philosopher’s View on Bayesian Evaluation of Informative Hypotheses. In: Hoijtink, H., Klugkist, I., Boelen, P.A. (eds) Bayesian Evaluation of Informative Hypotheses. Statistics for Social and Behavioral Sciences. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09612-4_16
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DOI: https://doi.org/10.1007/978-0-387-09612-4_16
Publisher Name: Springer, New York, NY
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